• DocumentCode
    2964704
  • Title

    Multi-camera Monitoring of Infusion Pump Use

  • Author

    Gao, Zan ; Chen, Ming-yu ; Detyniecki, Marcin ; Wu, Wen ; Hauptmann, Alexander ; Wactlar, Howard ; Cai, Anni

  • Author_Institution
    Sch. of Inf. & Commun. Eng., BUPT, Beijing, China
  • fYear
    2010
  • fDate
    22-24 Sept. 2010
  • Firstpage
    105
  • Lastpage
    111
  • Abstract
    When patients operate a home infusion pump, they maybe make some mistakes, and it will be dangerous. To detect potentially life threatening errors, we design an assistance system based on observation by multiple cameras and robust spatio-temporal algorithm. Firstly, we record the video by multiple cameras when people use the infusion pump. Secondly, we use a robust MoSIFT algorithm, which detects interest points and encodes not only their local appearance but also explicitly models local motion, to describe the action. Thirdly, we recognize each individual human operating step in the use of an infusion pump to see if the patient has correctly performed the required actions in a safe sequence. The specific infusion pump used for evaluation requires 22 operation steps from 12 action classes. From the experiments show that our best classifier can obtains an average rate of 56%, and MoSIFT algorithm is robust and stable.
  • Keywords
    cameras; image motion analysis; image recognition; medical administrative data processing; patient care; video signal processing; MoSIFT algorithm; assistance system; home infusion pump use; human operating step recognition; multicamera monitoring; video recording; Cameras; Computer vision; Electron tubes; Hidden Markov models; Image motion analysis; Optical imaging; Optical pumping; Hidden Markov Model; Human Behaviour Recognition; Medical Devices; Multi-Camera; Physical Sensor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing (ICSC), 2010 IEEE Fourth International Conference on
  • Conference_Location
    Pittsburgh, PA
  • Print_ISBN
    978-1-4244-7912-2
  • Electronic_ISBN
    978-0-7695-4154-9
  • Type

    conf

  • DOI
    10.1109/ICSC.2010.58
  • Filename
    5628914